Presented By O’Reilly and Intel AI
Put AI to Work
April 29-30, 2018: Training
April 30-May 2, 2018: Tutorials & Conference
New York, NY

Why data management for deep learning computer vision is challenging

Moses Guttmann (Seematics)
4:00pm–4:40pm Wednesday, May 2, 2018
Implementing AI
Location: Beekman Parlor
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

  • CTOs

Prerequisite knowledge

  • Familiarity with deep learning, DevOps, and database concepts and methodologies

What you'll learn

  • Understand how to scale deep learning, the differences between deep learning and machine learning with regard to raw data, new database paradigms, and DevOps versus research in the near future of deep learning in production


One of the most important aspects of deep learning is the quality and quantity of the data used in the learning process. Moses Guttmann explores the problem and offers approaches to solve it.

Topics include:

  • How to create a data environment that is coupled with deep learning
  • Understanding the needs of deep learning scientists from the point of view of the enterprise
  • Creating an environment where datasets are shared seamlessly in the organization
  • Moving toward continuously growing labeled datasets
  • How to implement and integrate into deep learning training frameworks
  • New types of databases for an AI/DL world
  • What the future of databases holds

Moses Guttmann


Moses Guttmann is CTO and founder of Seematics, a company building a holistic deep learning platform. A 15-year computer vision and deep learning specialist, Moses is a seasoned business and product leader with a two-decade track record in leading and driving execution of large-scale, complex products in a multitude of disciplines. Previously, he founded an innovative semiautomatic 3D conversion company and built face recognition technologies and wavelet-based compression on embedded systems for various companies. He holds an MSc in computer science (cum laude) from Tel Aviv University.